Dawson Whitfield has been a graphic designer for 12 years, splitting his time between creating logos for small businesses and improving the app user experience for startups. Last summer, having completed another logo — a process that took about three weeks and cost the client $3,000 — he took a step back. “I felt like a glorified font picker,” he says. “It was frustrating. I was invested in this profession but I felt like I was getting in the way.”

In November 2016, he launched his own startup, Toronto-based Logojoy, an automated, online logo maker powered by artificial intelligence. In so doing, Whitfield has entered the newest and hottest area of AI research: generative systems.

“[Logojoy] is on the frontier between what’s possible with current technology and what’s emerging. This is the transition from systems that are for prediction versus systems that are actually creating things,” says Graham Taylor, associate professor and lead of the Machine Learning Group at the University of Guelph and academic director of Next AI.

Also on that frontier, Google, which launched Quick, Draw!, an AI experiment to see if a neural network can learn to recognize doodling, and Project Magenta, where researchers are trying to teach machines to create compelling art and music. Still, there haven’t been many commercial applications — at least not yet. “We don’t really know what we want from creative machines but [Logojoy] is an early example. AI will be like software in that it will impact every industry,” says Taylor.

That’s because AI and machine learning are all about machines being able to write computer programs automatically based on the data they receive. Because there is more data available than ever, those programs can be very specific to a company or a sector or even to a consumer.

“Instead of Amazon looking at the purchasing habits of every single individual and trying to write a program to recommend them products, it makes a lot more sense to write an algorithm to aggregate across the previous purchase data and share data across customers and do those personalizations automatically,” says Taylor.

Not surprisingly, IDC Research forecasts global revenue for cognitive and AI systems to hit US$12.5 billion in 2017, up 59.3 per cent from 2016. This is expected to jump to more than US$46 billion by 2020.

AI is disrupting even the most traditional industries in surprising ways. For example, Toronto-based Intuitive, Inc. is using AI technology to transform the global US$1 trillion-plus waste management industry. “Our vision is to empower a zero-waste world, where everything that is thrown away is recycled or reused and diverted away from landfills and oceans,” says cofounder Hassan Murad. He and cofounder Vivek Viyas, are developing smart waste bins that automatically route waste for recycling and composting using computer vision, robotics and machine learning. Murad and Viyas are in talks with Canadian municipalities and plan to have a pilot in place by the end of the year. The technology will also identify each piece of garbage. “We are able to generate granular insights on people’s consumption in real-time in a given location, so that waste can be used to inform marketing strategies,” says Murad.

On the other end of the waste spectrum, Krista Caldwell, cofounder of startup Deepnify, is using AI to eliminate waste from the food supply chain. “Most grocery stores use sophisticated software to predict demand in each location. That works well for items that have a stable shelf life but not so much for fresh produce,” says Caldwell. “Machine learning can process way more data — historical buying patterns, weather, distance to competitors, upcoming holidays, neighbourhood demographics — and find overlapping patterns to make more accurate forecasts.”

When it comes to creating with AI, Logojoy’s CTO Rares Crisan says the more people use it, the more the AI can understand how to approach design and what is appealing, and then use that information in the cycle of design. “The iterative progression will lead to more complex designs.”

Since its launch, 800,000 people have signed up, three million logos have been generated and 15,000 logos have been sold. “It’s just like working with a designer at a much lower cost point,” says Whitfield. “Users choose a sample logo, colours, symbols and within two minutes custom logos are generated. From there, the magic kicks in. If you want to see different fonts, we can show you 50 different versions of your logo with a different font. From there you can tweak. When you’re happy, you buy it.” Logojoy offers three packages, at US$20, US$65 and US$165.

“We’ve taken a hard look at our process and how far it can go and have come to the conclusion that it can do anything a designer can do: Logos, business cards, banner ads, restaurant menus, websites,” says Whitfield.